Digital dental examination and documentation

ABSTRACT

Systems and methods are disclosed for processing and storing acquired data relating to one or more dental conditions. The methods can include acquiring a first oral feature in a first data acquisition using a data acquisition device, determining a first oral feature first reference point from the first data acquisition, diagnosing a first dental condition upon confirming that the first oral feature first reference point is associated with the first dental condition, acquiring the first oral feature in a second data acquisition using the data acquisition device, determining a first oral feature second reference point from the second data acquisition, and tracking the progression of the first dental condition by determining a discrepancy between the first oral feature first and second reference points.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of application Ser. No. 16/435,028filed Jun. 7, 2019, which is a continuation of U.S. patent applicationSer. No. 15/710,469 filed Sep. 20, 2017 (now U.S. Pat. No. 10,357,342),which claims the benefit of U.S. Provisional Application No. 62/397,504filed Sep. 21, 2016, and U.S. Provisional Application No. 62/397,525,filed Sep. 21, 2016, the contents of which are incorporated herein byreference in their entireties for all purposes.

BACKGROUND 1. Technical Field

This disclosure relates generally to the field of electronic dentalexamination and documentation and more specifically to systems andmethods that can electronically evaluate detected oral features anddocument the results.

2. Background of the Art

Comprehensive dental examinations should be a very thorough, detailed,and well-documented procedure. However, due to the rigors associatedwith the volume of information that accompanies dental examinations, itis well known that dentists often do not complete a thorough examinationand/or do not adequately document their findings and observations. It isgenerally known as well that dental examinations can and should includethe evaluation of periodontal tissues and functional deficiencies inaddition to dental structures and diseases. However, functionaldeficiencies and periodontal structures are often overlooked due to thedifficulty in quantifying them or being able to map them over time.

Previous efforts to improve this field have more narrowly focused ondiagnosing other dental problems (i.e., those other than functionaldeficiencies and/or those unrelated to periodontal tissues), patienteducation of the problems, helping the patient understand the problems,determining the extent of the problems, and making future prognoses.However, those efforts have all come up short with respect to electronicanalysis of acquired (e.g., scanned, photographed) dental data toidentify, quantify, map, and define the extent of dental structures,diseases and deficiencies, especially in relation to functionaldeficiencies and periodontal structures. The current state of the art isfor a dentist to make note of a condition, visually estimate the extentof the problem, and then decide to either treat or monitor thecondition, for example, by looking at scan results or radiographs on acomputer screen. However, if the dentist decides to monitor thecondition (as opposed to treating it), there is no way for the dentistto accurately determine if the problem is progressing or has progressedat the patient's next dental exam other than going by the patient'ssymptoms or a change in radiographs.

Therefore, a solution is needed for systems and methods that canaccurately diagnose conditions associated with hard and soft dentaltissues alike, including dental structures, diseases, and deficiencies,and which can evaluate, quantify and/or map such conditions, includingperiodontal structures and/or functional deficiencies. Such a solutionshould be able to quantify and map the extent of these conditions andestimate the quantity of tooth substance loss at the time of the exam orhistorically over time. Such a solution should also be able to processdata from dental data acquisition devices (e.g., from scanners) toanalyze and determine the extent of the conditions (e.g., the extent ofthe tooth substance loss) as well as give an accurate appraisal of thequantity of tooth substance loss (e.g., the mass or volume of the loss).Such solutions are needed to provide accurate electronic dental recordsand comprehensively diagnose all existing conditions. A need exists toimprove the programming of current processors so that such data analysisis possible. A need also exists for systems and methods that can executeboth a physiologic and functional analysis of dental tissues andstructures from acquired data.

BRIEF SUMMARY OF THE INVENTION

This disclosure relates generally to electronic dental examination anddocumentation.

More specifically, systems and methods are disclosed that canelectronically evaluate detected oral features and analyze and documentthe results.

Briefly, systems and methods are disclosed that utilize digitallygathered information (e.g., from scans, radiographs, photographs, or anycombination thereof) to identify and document existing dentalstructures, diseases and deficiencies for use in baseline documentation,historical mapping, comparisons to the norm, diagnosis, prognosis,treatment planning and data libraries, and for the creation ofcomprehensive electronic dental records.

The methods disclosed can include methods for electronically diagnosingand tracking the progression of one or more dental conditions. Forexample, a method is disclosed that can include acquiring a first oralfeature in a first data acquisition using a data acquisition device. Themethod can include determining a first oral feature first referencepoint from the first data acquisition. Determining the first oralfeature first reference point can include using a processor. The methodcan include diagnosing a first dental condition upon confirming that thefirst oral feature first reference point is associated with the firstdental condition. The method can include acquiring the first oralfeature in a second data acquisition using the data acquisition device.The method can include determining a first oral feature second referencepoint from the second data acquisition. Determining the first oralfeature second reference point can include using the processor. Themethod can include tracking the progression of the first dentalcondition by determining a discrepancy between the first oral featurefirst and second reference points.

The methods disclosed can include methods for electronically diagnosingand tracking the progression of one or more dental conditions. Forexample, a method is disclosed that can include determining a dentalcondition first reference point and a dental condition second referencepoint. Determining the dental condition first and second referencepoints can include processing first and second data sets, respectively,received from a data acquisition device. The method can includediagnosing the dental condition upon confirming that the dentalcondition first and/or second reference point is associated with thedental condition. The method can include tracking the progression of thedental condition by determining a discrepancy between the dentalcondition first and second reference points.

The systems disclosed can include dental condition diagnosis andtracking systems. For example, a system is disclosed that can include adata acquisition device. The system can include an examination unit. Theexamination unit can be configured to process first and second data setsreceived from the data acquisition device to determine a dentalcondition first reference point and a dental condition second referencepoint, respectively. The examination unit can be configured to diagnosethe dental condition upon confirming that the dental condition firstand/or second reference point is associated with the dental condition.The examination unit can be configured to track the progression of thedental condition by determining a discrepancy between the dentalcondition first and second reference points.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings shown and described are exemplary embodiments andnon-limiting.

Like reference numerals indicate identical or functionally equivalentfeatures throughout.

FIG. 1 illustrates a schematic of a variation of an electronic dentalexamination and documentation system.

FIGS. 2A-2E illustrate a diagrammatic representation of a variation ofdental attrition formation.

FIG. 3 illustrates a diagrammatic representation of a variation ofabfraction and/or abrasion at the cervical margin of a tooth.

FIG. 4 illustrates a diagrammatic representation of a variation ofchemical erosion of a tooth.

FIG. 5 illustrates a diagrammatic representation of two variations ofteeth with wear.

FIG. 6 illustrates a diagrammatic representation of a variation offractured teeth and fracture lines.

FIG. 7 illustrates a diagrammatic representation of a variation ofmicrodontia, supernumerary teeth and fusion of teeth.

FIG. 8 illustrates a diagrammatic representation of a variation of amissing tooth and an edentulous space.

FIGS. 9A-9D illustrate diagrammatic representations of variations ofdifferent restorative materials for dental restorations,demineralization, decay and re-current decay.

FIG. 10 illustrates a diagrammatic representation of a variation ofvarious periodontal structures including the gingival margin (GM),furcation, mucogingival line (MGL), recession, and minimally attachedtissue (MAT).

FIG. 11 illustrates a variation of a process undertaken by the system.

FIG. 12 illustrates a variation of an algorithm executed by the system.

FIG. 13 illustrates a variation of a process undertaken by the system.

FIG. 14 illustrates a variation of an algorithm executed by the system.

DETAILED DESCRIPTION

Systems and methods are disclosed that can electronically evaluate anddocument oral features, including dental features, periodontal features,craniofacial features, or any combination thereof. The systems andmethods disclosed can examine, analyze, diagnose and document dentalstructures, deficiencies, and/or diseases, as well as any othercondition relating thereto, for example, any condition relating to themasticatory system. Dental structures, deficiencies and diseases areindividually and collectively referred to throughout as features andconditions.

The systems and methods disclosed can identify, quantify, analyze and/ormap existing conditions, predict the progression of existing conditions,provide a probability for the manifestation of currently non-manifestedconditions, provide a recommendation to treat and/or monitor existingconditions, provide a recommendation to treat and/or monitor not yetmanifested conditions (e.g., with preventative treatment), identifyvariables that are contributing to and causing the development ofexisting and not yet manifested conditions, identify educationalprotocols that can influence and succeed in changing patient behaviorthat is causing or is detrimental to dental health or its improvement,identify educational protocols most likely to influence and succeed inchanging behavior that is causing or is detrimental to dental health orits improvement specific to the patient, for example, based partly orcompletely on physiologic, genetic, bacterial, and environmentalfactors, as well as their health history, or any combination thereof.For example, the systems and methods disclosed can measure, map,diagnose, and/or define the extent of dental deficiencies as well as anyother detectable (e.g., scannable, photographable) dental conditions.The mappings disclosed can be visual (e.g., using one-, two-, three-,and/or four-dimensional representations) and/or numeric (e.g., usingnumbers, ratios, and/or matrices). Three- and four-dimensionalrepresentations, for example, can be 3D printed structures and/or 3Dcomputer renderings, with the four-dimensional printed structures and/orrenderings including time and/or date indicators. The mappings disclosedcan be used to create historical, current, and/or predictive models forthe acquired (e.g., scanned, x-rayed, photographed) conditions and/or ofhealthy structures not associated with a condition.

The systems and methods disclosed can perform structural, physiological,and/or functional analyses of existing conditions. The systems andmethods disclosed can analyze data captured from one or multiple dataacquisition devices (e.g., one or multiple scanning devices, imagecapturing devices, video capturing devices, or any combination thereof)and/or systems. For example, the systems and methods disclosed cananalyze data recorded by one or multiple intra-oral data acquisitiondevices (e.g., one or multiple intra-oral scanners, radiograph devices,camera devices, or any combination thereof).

The methods disclosed can include algorithms that can be executed by thesystem. The algorithms disclosed can use data recorded by and/orretrieved from the one or multiple data acquisition devices and/or froma database, memory, or other storage medium that has the recorded datastored thereon. The algorithms disclosed can measure or otherwisequantify the extent of the areas affected by a condition. The algorithmsdisclosed can measure or otherwise quantify the extent of the conditionson one or more teeth, for example, on each tooth individually and/or onmultiple teeth sequentially and/or simultaneously. The resultant datacan be used visually on the existing image or digital representation(e.g., by superimposing the data or a derivative of it on the existingimage or digital representation) and/or can be used in a numericformulation on a tooth-by-tooth and/or entire dentition summary. Forexample, the resultant data can be used visually on an existing scan(e.g., a previous scan obtained at an earlier patient visit), forexample, by superimposing the data or a derivative of it on the earlieracquired scan.

The systems and methods disclosed can electronically document orotherwise store examination and/or analysis results for use in baselinedocumentation, mapping (e.g., historical mapping, current mapping,predictive mapping), statistical comparisons (e.g., comparisons to thenorm), diagnosis, treatment planning, patient education, or anycombination thereof. The electronically documented or otherwise storeddata can be queried or otherwise retrieved during the evaluation andanalysis of subsequent data acquisitions (e.g., scans, radiographs,photographs) to be able to accurately determine the progression of thepreviously examined conditions, for example, by comparing results of asubsequent data acquisition to the results of one or more previous dataacquisitions. The results of a data acquisition (e.g., the initial dataacquisition and/or one or more subsequent data acquisitions) can becompared to results previously obtained from the same patient and/orfrom one or more different patients. The system and methods disclosedcan have and/or can build a library of patient-specific and non-patientspecific examination and analysis data. Such libraries of data can allowone-time data acquisitions and/or each subsequent data acquisition to bemore informative to the patient and medical professional alike. Theelectronically stored data can allow the system to build dentalnarratives for one or multiple teeth that can be quickly referenced andprovide critical details regarding a person's health that visualinspection of data acquisition results would not provide alone.

The systems and methods disclosed can utilize artificial intelligenceand/or machine learning when processing acquired data (e.g., scan data,radiographic data, photograph data), including programming one or moreprocessors with artificial intelligence and/or machine learningsoftware.

In this way, the systems and methods disclosed can provide comprehensivedental examinations that are both accurate and reliable, and whichenable existing and not yet manifested conditions to be more easily,accurately, and precisely tracked over time.

The various exemplary variations of the systems and methods disclosedcan be interchangeably combined with any other variation disclosed andcontemplated herein. Likewise, the various components, features,elements, processes, steps, and/or operations of each exemplary systemand/or method disclosed can be interchangeably combined with any othervariation disclosed and contemplated herein Although every iteration ofthe systems and methods disclosed has not been expressly illustrated inthe accompanying figures, it will be understood that the accompanyingfigures are exemplary and non-limiting, and that while absence of afeature does not require its omission, it nevertheless discloses itsomission, and hereby provides support for potential future negativelimitations in the claims. Any disclosure herein can be combined ormodified with any other disclosure herein, even if such a combination isnot expressly illustrated in the accompanying figures, as theaccompanying figures are exemplary only.

System

FIG. 1 illustrates a schematic of a variation of an electronic dentalexamination and documentation system 100. The system 100 can have a dataacquisition device 102 and an examination unit 104. The data acquisitiondevice 102 can be in wired or wireless communication with theexamination unit 104. One or more data acquisition devices 102 can beconnected to the examination unit 104. The examination unit 104 canreceive data from one or more data acquisition devices 102, for example,separately, sequentially, and/or simultaneously. The data acquisitiondevice 102 can be used to capture or image (e.g., scan, photograph,x-ray) the various oral features disclosed herein, including dentalfeatures, periodontal features, craniofacial features, or anycombination thereof, including the various hard and soft tissuesassociated with each. FIG. 1 illustrates that the data acquisitiondevice 102 can acquire the oral features of a patient 101, for example,by electronically capturing or imaging the oral features. The acquiringis indicated by the dotted line that extends between the patient 101 andthe data acquisition device 102. The dotted line also represents wiredor wireless data transfer to and/or from the data acquisition device 102and the examination unit 104.

The data acquisition device 102 can be used to create a digitalimpression of all or part of an oral cavity and the masticatory system.For example, the digital data that the data acquisition device 102acquires can digitally represent one or more oral features, includingthe entire dentition, a subset thereof, a single tooth, one or moreportions of multiple teeth, a portion of a single tooth, the supportingperiodontal and/or craniofacial structures, nerve innervation, bloodvessel perfusion, or any combination thereof. In this way, the dataacquisition device 102 can be used to digitally record the existingconditions of an oral cavity and the masticatory system, includinghealthy and unhealthy conditions, as well as conditions that areimproving or deteriorating.

The data acquired by one or multiple data acquisition devices 102 can bemerged or otherwise combined into a single digital representation (e.g.,image), can be kept separate, or can be partitioned and/or combined intomultiple digital representations (e.g., images). One or more aspects(e.g., one or more dental features or conditions) recorded by one ormultiple data acquisition devices 102 can be merged or otherwisecombined into a single digital representation (e.g., an image), can bekept separate, or can be partitioned and/or combined into multipledigital representations (e.g., images). For example, multiple data setsacquired by one or multiple data acquisition devices 102 can be mergedor otherwise combined into a single digital representation (e.g.,image), can be kept separate, or can be partitioned and/or combined intomultiple digital representations (e.g., images), as can multiple datasets representative of one or more aspects (e.g., one or more dentalfeatures or conditions) recorded by one or multiple data acquisitiondevices 102.

The data acquisition device 102 can be a scanner, an x-ray device, acamera, or any combination thereof. For example, the data acquisitiondevice 102 can be a handheld scanner, radiographic imaging device,camera, or any combination thereof. Additionally or alternatively, thedata acquisition device 102 can be a scanner, radiographic imagingdevice, or camera mountable (e.g., mounted) to a wall, floor, and/orceiling. For example, the system 100 can have or can be capable ofutilizing (e.g., receiving data recorded by) one or multiple intra-oralscanners, and/or one or multiple other data acquisition devices. Thedata acquisition device 102 can be a 3D scanner (e.g., 3D videoscanner), a computed tomography (CT) scanner, a confocal imagingscanner, a parallel confocal imaging scanner, a light emitting diode(LED) pattern projection scanner, a laser scanner, a radiographicscanner, or any combination thereof. One or multiple (e.g., two, three,four or more) types of data acquisition devices 102 can be used toacquire dental data for dental condition detection and evaluation. Thenumber and type of data acquisition devices 102 used can depend on theconditions that are sought to be detected, for example, whether softand/or hard tissues need to be detected, such that the number and typeused can advantageously be made on a case-by-case basis to accommodateeach person's needs.

The data acquisition device 102 can record digital data having one ormultiple images, data slices, and/or videos. The data acquisition device102 can provide data having any file format, for example,stereolithography (STL) files, DCM files having a DICOM format, graphicinterchange format (GIF) files, joint photographic experts group (JPEG)files, tagged image files (TIF), and/or portable network graphics (PNG)files. Such data cannot be prepared in the mind of a dentist andtherefore provides more accurate and reliable results than when comparedto visual inspection alone.

The examination unit 104 can process data received and/or retrieved fromthe data acquisition device 102. For example, the examination unit 104can process images and videos or any other processable representationrecorded by the data acquisition device 102. The examination unit 104can process videos and/or slice video data into one or more smallersized still images. The examination unit 104 can process acquired datain real-time and/or can process acquired data that was previouslystored, for example, in a computer readable storage medium.

The one or more data acquisition devices 102 and the examination unit104 can provide a comprehensive electronic examination of one ormultiple patients (e.g., patient 101).

The examination unit 104 can be local or remote relative to the dataacquisition device 102. For example, the examination unit 104 can be onor be part of a server such as a cloud server, a cluster server, and/ora storage server. The examination unit 104 can analyze data from one ormultiple data acquisition devices 102 and can be configured to store rawdata (e.g., unprocessed data, unanalyzed data), processed data, dataderived from raw and/or processed data, or any combination thereof, forexample, on a server or on a local memory medium. In this way, theexamination unit 104 can electronically “document” examination resultsand any analyses thereof that can be later referenced by the patient, amedical professional (e.g., dentist), the data acquisition device 102,and/or the examination unit 104. Such storage can be useful forestablishing an initial baseline data acquisition that can be analyzedto determine one or more reference points that can be stored to latercompare to one or more reference points of one or more subsequent dataacquisitions (e.g., scans, radiographs, photographs), thereby enablingelectronic tracking and observation of the dentition, the supportstructures and surrounding tissues, and the conditions, diseases, and/orconditions thereof. The references points can be numerical or visualrepresentations. For example, the reference points can be one or more ofthe quantifications and/or mappings described herein (e.g., referencelocations, reference measurements, reference shapes, reference ratios,reference colors, shades, or tints, reference blood perfusion, or anycombination thereof).

FIG. 1 further illustrates that the examination unit 104 can have aprocessing unit 106, a memory unit 108, and a communication unit 110.The processing unit 106 can be coupled to the memory and communicationunits 108, 110 through high-speed buses.

The processing unit 106 can include one or more central processing units(CPUs), graphical processing units (GPUs), application-specificintegrated circuits (ASICs), field-programmable gate arrays (FPGAs), orany combination thereof. The processing unit 106 can execute softwarestored in the memory unit 108 to execute the methods, instructions,and/or algorithms described herein. The processing unit 106 can beimplemented in a number of different manners. For example, theprocessing unit 106 can be an embedded processor, a processor core, amicroprocessor, a logic circuit, a hardware finite state machine (FSM),a digital signal processor (DSP), or any combination thereof. As a morespecific example, the processing unit 104 can be a 32-bit or a 64-bitprocessor.

The memory unit 108 can store software, data, logs, or any combinationthereof. The data stored can be raw data, processed data, data derivedfrom raw and/or processed data, or any combination thereof. For example,the memory unit 108 can store data received from the data acquisitiondevice 102, as well as the output from the processing unit 106 after thedata acquisition device 102 data has been analyzed and/or modeled. Thememory unit 108 can be an internal memory of the examination unit 104 asshown in FIG. 1, or it can be an external memory, such as a memoryresiding on a storage node, a cloud server, and/or a storage server.

The memory unit 108 can be a volatile memory or a non-volatile memory.For example, the memory unit 108 can be a non-volatile storage mediumsuch as non-volatile random access memory (NVRAM), flash memory, diskstorage, or a volatile storage such as static random access memory(SRAM). The memory unit 108 can be the main storage unit for theexamination unit 104.

The communication unit 110 can include one or more wired or wirelesscommunication interfaces. For example, the communication unit 110 can bea network interface card of the examination unit 104. The communicationunit 110 can be a wireless modem or a wired modem, for example, a WiFimodem, a 3G modem, a 4G modem, an LTE modem. Alternatively, or incombination, the communication unit 110 can be a Bluetooth™ component, aradio receiver, an antenna, or any combination thereof. For example, thecommunication unit 110 can be a server communication unit. Theexamination unit 104 can transmit and/or receive data packets and/ormessages using the communication unit 110. The communication unit 110can connect to or communicatively couple with one or more wirelesssignal transceivers and/or networks.

The examination unit 104 can include an external database 112 separatefrom, alternative to, and/or additional to the memory 108. The memory108 and/or the database 112 can be internal and/or external to theexamination unit 104, and can each be non-volatile and/or volatilememory. Alternatively, or in combination, the database 112 can beintegrated or otherwise combined with the memory 108. The externaldatabase 112 can be on or be part of a server, for example, a cloudserver, and/or a storage server.

The memory 108 and/or the external database 112 can be configured tostore patient-specific data and/or non-patient specific data. Forexample, the memory 108 can store patient-specific data and the externaldatabase 112 can store non-patient specific data recorded from one ormore patients different from patient 101.

The examination unit 104 can have one or multiple processing units 106,memories 108, communication units 110, and/or external databases 112.

FIG. 1 also illustrates that the system 100 can have one or moredisplays 114. The display 114 can display data acquisition resultsand/or the analyses and mappings thereof. The display 114 can beintegrated with the device or system having the examination unit 104and/or can be part of a standalone device in wired or wirelesscommunication with the examination unit 104. For example, the display114 can be part of a computer, a smartphone, a tablet, a laptop, asmartwatch, or any combination thereof. The device having the display114 can be in communication with the data acquisition device 102, one ormore other devices, the cloud, and/or one or more networks.

Alternatively, or in combination, the examination unit 104 can be partof or integrated with the device or system having the display 114,including a personal or portable device, for example, a computer, asmartphone, a tablet, a laptop, a smartwatch, or any combinationthereof. Executable code can be installed on memory (e.g., memory 108)of the device having the display 114. When the executable code isexecuted by the device, the device can perform the instructions,processes, methods, and operations disclosed and contemplated herein,such that the device can analyze data acquisition results. For example,a smartphone application can be downloaded onto a smartphone that hasexecutable code configured to carry out the various functions of theexamination unit 104. Alternatively, or in combination, executable codecan be located on the cloud, for example, on a server. The device (e.g.,a smartphone) can query the server to run the executable code on theserver to carry out the instructions, processes, methods, and operationsdisclosed and contemplated herein.

Alternatively, or in combination, the examination unit 104 can comprisedownloadable executable code that utilizes existing processing, memory,and data storage features of a device and/or the cloud.

As described above, the examination unit 104 can analyze data capturedby one or multiple data acquiring devices and/or systems 102, forexample, from one or multiple intra-oral data acquisition devices 102.The examination unit 104 can analyze data from one or multiple dataacquisition devices 102 sequentially and/or simultaneously. Theexamination unit 104 can detect (and distinguish between) healthy and/orunhealthy conditions from the acquired data received, accessed, and/orprocessed (e.g., scans, radiographs, images, photographs, and/or video).The examination unit 104 can electronically quantify and map the oralcavity, dentition, and supporting hard and soft tissue structures. Theexamination unit 104 can use these quantifications and mappings to makediagnoses, predictions (e.g., prognoses), and treatment recommendations,as well as for designing treatment plans. For example, the processingunit 106 can identify, quantify, analyze and/or map existing conditions,predict the progression of existing conditions, provide a probabilityfor the manifestation of currently non-manifested conditions, provide arecommendation to treat and/or monitor existing conditions, provide arecommendation to treat and/or monitor not yet manifested conditions(e.g., with preventative treatment), identify variables that arecontributing to and causing the development of existing and/or not yetmanifested conditions, identify educational protocols that can influenceand succeed in changing patient behavior that is causing or isdetrimental to dental health or its improvement, identify educationalprotocols most likely to influence and succeed in changing behavior thatis causing or is detrimental to dental health or its improvementspecific to the patient, for example, based partly or completely onphysiologic, genetic, bacterial, and environmental factors, as well astheir health history, or any combination thereof.

Using the processing unit 106, the examination unit 104 can quantify(e.g., measure), map (e.g., model), diagnose, and/or define the extentof dental deficiencies (e.g., functional deficiencies) as well as anyother detectable (e.g., scannable, radiographable, photographable)dental conditions. While acquired data can provide a snapshot of thepresent, the processing unit 106 can “examine” (i.e., analyze) theacquired data to build a “picture” of past and future states withpredictive and speculative modeling techniques such as statisticalanalysis involving comparisons to the norm and other data sets in whichthe past, present, and/or future states are already known (e.g., fromother patients having conditions in the same or different stages and/orhaving interrelated causes to those conditions being treated ormonitored in patient 101). This picture can come in the form of visualand/or numerical mappings as described in more detail below.

The statistical analysis can involve computing one or more statisticalparameters, for example, maximums, minimums, medians, averages, norms,standard deviations, or any combination thereof. The statisticalanalysis can involve generating one or more statistical distributions,for example, discrete probability distributions and/or continuousprobability distributions (e.g., normal/Gaussian distributions). Thequantifications and mappings can be analyzed to determine one or morestatistical parameters and/or to generate one or more statisticaldistributions. The quantifications and mappings can be statisticalparameters and/or distributions. For example, the reference pointsdetermined from the data acquisitions can be statistical parametersand/or distributions.

The system 100 (e.g., the examination unit 104) can measure or computeone or more quantities associated with the acquired data, for example,dimensions, quantities associated with qualitative (e.g., color)characterizations, and statistical parameters. For example, the system100 (e.g., the examination unit 104) can measure or compute one or morequantities representative of or associated with one or more anatomicalmarkers and/or patterns (e.g., exact and/or estimated peaks, valleys,geometries, shapes, lines, perimeters, outlines, or any combinationthereof), the relative positions of anatomical markers and/or patterns(e.g., the distances between them, their sizes), the relative positionsof dental conditions (e.g., the distances between them, their sizes),the relative positions of hard and soft tissues (e.g., the distancesbetween them, their sizes), light absorption, light reflection, colors(e.g., hues), tints, tones, and shades of colors (e.g., light, medium,and/or dark shades of a hue), changes in any of the foregoing, or anycombination thereof.

The system 100 (e.g., the examination unit 104) can generate visualmappings (e.g., using one-, two-, three-, and/or four-dimensionalrepresentations) and/or numeric mappings (e.g., using numbers, ratios,and/or matrices) of the acquired data, for example, one or more of thedental conditions digitally represented by the acquired data. The visualand/or numeric mappings can include healthy, diseased, and/or deficientstructures and tissues. The system 100 can generate or can produce andsend instructions to generate one or more one-, two-, three-, and/orfour-dimensional representations of acquired data (e.g., a scan, aradiograph, a photograph). The three- and four-dimensionalvisualizations can be, for example, 3D printed structures and/or 3Dcomputer renderings, with the four-dimensional printed structures and/orrenderings including time and/or date indicators thereon. The mappingscan be used to create historical, current, and/or predictive models forthe conditions digitally captured by the data acquisition device 102and/or of healthy structures not associated with a condition. Themappings can be statistical distributions.

Quantifying and/or mapping the oral cavity and masticatory system caninvolve determining one or more reference parameters or regions(collectively referred to throughout as reference points). Eachreference point can be quantitative or qualitative. Each reference pointcan be a numerical representation and/or a visual representation of adental condition. For example, the reference points can correspond toone or more reference locations, reference contacts, reference contactregions, reference contact points, reference contact surfaces (e.g.,reference occlusal surfaces), reference measurements, reference shapes,reference ratios, reference colors, shades, or tints, reference bloodperfusion, or any combination thereof. The reference contacts andreference contact regions/points/surfaces identified by the system 100can be on a single tooth or can be the areas of engagement between twoteeth (e.g., a maxillary tooth and a mandibular tooth). The referencepoints can correspond to soft tissue having certain characteristicsand/or hard tissue having certain characteristics. Such certaincharacteristics can include, for example, the size, shape, quantity(e.g., mass, volume, etc.), coloration, level of vascular perfusion,structure, structural integrity, or any combination thereof, of softand/or hard tissue. For example, the reference points can correspond toone or more anatomical markers and/or patterns (e.g., exact and/orestimated peaks, valleys, geometries, shapes, lines, perimeters,outlines, contacts, contact regions/points/surfaces, or any combinationthereof), the relative positions of soft and/or hard tissues relative toone another (e.g., the relative positions of one or more anatomicalmarkers to one or more other of the same or different anatomicalmarkers), light absorption, light reflection, colors (e.g., hues),tints, tones, and shades of colors (e.g., light, medium, and/or darkshades of a hue), changes in any of the foregoing, or any combinationthereof. For example, the examination unit 104 can differentiatebetween—and can measure, map, or otherwise determine the extentof—plaque, enamel, dentin, pulp, gum, cement, nerves (e.g.,innervation), blood vessels, bone, restorative materials, bacteria, orany combination thereof. The reference point identified by the system100 can be exposed dentin, for example an exposed spot or area ofdentin. As another example, the examination unit 104 can differentiatebetween the crown, neck, and/or root of each tooth, and can measure,map, or otherwise determine the extent of each. The reference pointidentified by the system 100 can be a ditch around the cervical margin.The distance between reference points can be determined by comparing afirst and a subsequent reference point, for example using photogrammetrytechniques. The reference points can be the quantifications and mappingsdescribed herein. The reference points can be separate from thequantifications and mappings described herein. The reference points canbe derived (e.g., via the examination unit 104) from the quantificationsand mappings described herein. To determine the reference points, thesystem 100 can determine one or more potential reference points, forexample, by determining a potential subsequent (e.g., maximum) extent ofthe of the reference point.

The reference points can be independent from one another, for example,such that each reference point can be separately displayed orcommunicated to a user. The reference points can be layered (e.g.,simultaneously displayed or communicated to a user). For example, one ormore reference measurements can be displayed on a 2D visualrepresentation of the dentition having colors indicative of where eachdental condition is located. Each type of a dental condition can beassociated with a different color, shade, tint, or hash markings.

The reference points of two different data acquisitions (e.g., a firstdata acquisition and a subsequent data acquisition) can be compared withone another to determine the progression of the identified conditions,including more than two data acquisitions (e.g., 3 to 50 dataacquisitions, or more narrowly, 3 to 20 data acquisitions, or morenarrowly still, 3 to 10 data acquisitions, or even more narrowly, 3 to 5data acquisitions). This advantageously enables electronic tracking andobservation of the dentition, the support structures and surroundingtissues, and the conditions, diseases, and/or conditions thereof.

The reference points can be a reference region that includes only thearea or condition of interest (e.g., a contact area, exposed dentin,wear surface, or any combination), or a region slightly beyond the areaor condition of interest. For example, a two-dimensional shape (e.g., acircle, an ellipse, a hemisphere, a triangle, square, rectangle,pentagon, hexagon, or other polygonal shape, including a series ofconnected line segments forming a closed shape, where the line segmentscan be straight and/or form one or more arcs), or a three-dimensionalshape (e.g., sphere, spheroid, hemispheroid, ellipsoid, or three-,four-, five, six-, seven-, or more-sided prism) can extend around (e.g.,around a center, a first end, a second end) of the area/condition ofinterest in a cross-sectional view and a three-dimensional view,respectively. The two- or three-dimensional shape can include thearea/condition of interest and an area beyond that area. For example,the shape can extend at a constant or variable distance beyond aboundary of the contact area, for example, from about 0.1 mm to about5.0 mm, including every 0.1 mm increment therebetween. Using atwo-dimensional shape to surround the area or condition of interest in aside or cross-sectional view and/or a three-dimensional shape tosurround the area or condition of interest in a three-dimensional viewallows the reference point to be approximated.

Quantifying and/or mapping the oral cavity and masticatory system caninvolve determining one or more potential reference parameters orregions (collectively referred to throughout as potential referencepoints). The potential reference points can be smaller or larger thanthe first and second reference points. The system 100 can estimate oneor more potential reference points, for example, based on one or moredetermined reference points, and/or based one or more other aspects ofdata acquired by the data acquisition device 102. The system 100 candetermine one or more potential reference points from an analysis ofdata acquisition data, from which the system 100 can determine one ormore corresponding actual reference points (simply referred tothroughout as “reference points”). The actual reference points can besized so that the corresponding potential reference points do not change(e.g., in size, in shape) between two adjacent data acquisitions. Thepotential reference points can provide the system 100 with a referencefrom which to anchor an analysis of a subsequent data acquisition, forexample for calibration. The potential reference points can have anytwo-dimensional or three-dimensional shape as described above withrespect to the reference points. The potential reference points can havethe same or a different shape than the actual reference points. Thereference and potential reference points can each have the same shape asor a different shape than another reference or potential referencepoint. The system 100 can determine a potential reference point forevery reference point that is determined.

The system 100 (e.g., the examination unit 104) can predict themanifestation of not yet manifested conditions, for example, basedpartly or completely on physiologic, genetic, environmental, and/orbacterial factors, as well as their health history. The system canpredict dental conditions, diseases, and deficiencies, for example,those described herein.

For example, to make predictions regarding when a not yet manifestedcondition will likely manifest, for example, with physical symptoms, theprocessing unit 106 can evaluate the variables identified ascontributing to the identified existing conditions. The processing unit106 can then determine the likelihood that a non-manifested conditionthat relates to or is associated with one or more of those variableswill manifest in the future as an observable or otherwise detectablecondition (e.g., within about 1-12 months or more, sometime within thenext 1 year, 2 years, 3 years, 4 years, 5 years, 10 years, 15 years, or20 or more years). Alternatively, or in combination, the processing unit106 can evaluate other factors such as age and diet to predict thelikelihood of a currently that a non-manifested condition will becomeobservable in the future and/or predict the speed of its subsequentprogression after becoming observable. The processing unit 106 canestimate the expected extent and/or location of the not yet manifestedcondition when it becomes observable, for example, by making one more ormore underlying assumptions regarding a patient's physiology and/orbehavior, the environment, and/or current treatment (e.g., no change, asmall, moderate, and/or large change in current physiology, behavior,and/or environment, in addition to the success or failure rate ofcurrent treatments, if any, the projected treatment progression ofeither success, failure, and/or no change, and/or recorded or otherwiseobserved progression of the current treatment).

The system 100 (e.g., the examination unit 104) can diagnose dentalconditions, diseases, and deficiencies, for example, those describedherein.

The system 100 (e.g., the examination unit 104) can determine whether totreat or monitor one or more detected conditions, and/or can recommend acourse of action to that effect. For example, the system 100 cangenerate a treatment recommendation whenever a diagnosis value isgreater than or equal to a treatment threshold, and can generate amonitor recommendation whenever a diagnosis value is less than thetreatment threshold. The treatment threshold can be tied to benchmarkvalue that is applicable across patients, or the treatment threshold canbe specific to the patient. The treatment threshold can correspond to apercentage deterioration (or estimation thereof) and/or a stage of thecondition (or estimation thereof). For example, the system 100 cangenerate a treatment recommendation for percentage deteriorations ofabout 5% or more (where 0% corresponds to zero deterioration), 10% ormore, 15% or more, or 20% or more. The system 100 can generate atreatment recommendation of conditions that are in a treatable stage.

The system 100 (e.g., the examination unit 104) can design educationalprotocols/plans that can influence and succeed in changing patientbehavior that is causing or is detrimental to dental health or itsimprovement. For example, the system 100 can identify educationalprotocols most likely to influence and succeed in changing behavior thatis causing or is detrimental to dental health or its improvementspecific to the patient, for example, based partly or completely onphysiologic, genetic, bacterial, and environmental factors, as well astheir health history. The educational plans can include suggestedreading material and video tutorials about the conditions a patient hasand/or is at risk of having, a review schedule for the materials andtutorials, reminders regarding dental hygiene (e.g., brush teeth, floss,mouthwash, and the frequency of each), and cross-disciplinarycollaboration recommendations and status tracking with, for example,health coaches, lifestyle coaches, and dieticians.

In this way, the examination unit 104 can perform structural,physiological, and/or functional analyses of existing conditions, forexample, those identified by the processing unit 106, and then makediagnoses, predictions, and recommendations.

The electronic examination and documentation system 100 canelectronically document or otherwise store examination and/or analysisresults for use in baseline documentation, mapping (e.g., historicalmapping, current mapping, and/or predictive mapping), statisticalcomparisons (e.g., comparisons to the norm), diagnosis, treatmentplanning, patient education, or any combination thereof. Theelectronically documented or otherwise stored data can be queried orotherwise retrieved during the evaluation and analysis of one ormultiple subsequent data acquisitions (e.g., scans, x-rays, photographs)to be able to accurately determine the progression of previouslyexamined conditions, for example, by comparing the results of asubsequent data acquisition to the results of one or more previous dataacquisitions. The examination unit 104 can compare the results of a dataacquisition (e.g., the initial data acquisition and/or one or moresubsequent data acquisitions) to the results of one or more previouslyobtained data acquisitions from the same patient and/or from one or moredifferent patients. For example, the storage can be useful for storingan initial baseline data acquisition and comparing data associatedtherewith (e.g., quantifications, mappings, reference points) to one ormore subsequent data acquisitions (e.g., scans, radiographs,photographs), thereby enabling electronic tracking and observation ofthe dentition, the support structures and surrounding tissues, and theconditions, diseases, and/or conditions thereof.

The examination unit 104 can have and/or can build a library ofpatient-specific and non-patient specific examination and analysis data,for example, using memories 108 and 112. Such libraries of data canallow one-time data acquisitions and/or each subsequent data acquisitionto be more informative to the patient, medical professional, andexamination unit 104 alike. The electronically stored data can allow thesystem 100 to build dental narratives for one or multiple teeth that canbe quickly referenced and provide critical details regarding a person'shealth that visual inspection of data acquisition results (e.g., scans,radiographs, photographs) would not provide alone. These stories are notonly desirable for the dentist and/or the examination unit 104 to makediagnoses and/or prognoses (e.g., predictions/forecasts of theprogression of existing conditions) and to better educate patients, theyare also desirable because they give patients more freedom in selectingtheir dental care provider, as the initial ramp up period a new dentistmust undergo when welcoming a new patient to their practice is reducedby making a patient's history more accessible, understandable, andreadily digestible.

For example, the quantifications and mappings disclosed herein can allowdentists to more readily review a patient's dental health and history“at a glance”—a fully accurate and precise comprehensive glance—asopposed to the more laborious method of pouring over old paper records,reviewing lengthy digital records comprising rushed or incompletedentist/medical notes, or visually reassessing an endless collage of rawacquired data in which a new set of eyes must confirm or re-confirm pastwork. The examination unit 104 can focus a dentist's attention on what'simportant, for example, by assigning different weights to differentconditions, for example, based on the type, severity (e.g., extent),and/or stage of the condition. Such weights can correspond to differentsections in the electronic dental data (e.g., electronic medical record)that the examination unit 104 can store, different text colors in theelectronic dental record, different indicators on the one or more of thegenerated mappings and quantifications such as colors, symbols,magnified views, colored shapes (e.g., a red rectangle around importantconditions and/or quantifications) and the like, as well as differentindicators associated with the one or more generated mappings andquantifications such audible warnings or messages that are emitted, forexample, automatically when that condition is being viewed or manuallywhen a user clicks on the display 114 or touches the screen 114 to“play” the warning or message. The system 100 can therefore makedentists more efficient, patients more knowledgeable and dentaltreatments more successful and fulfilling. This improved efficiency thatthe system 100 provides can in turn encourage patients to find thosecare providers who they are most comfortable with, or otherwise empowerthem to be more inclined to leave those care providers the patient maybe unhappy with for one reason or another, as it reduces the amount ofnon-transferrable information that is lost when a patient switches fromdentist to another. For the same reasons, the system 100 makes finding anew dentist, for example, due to geographic relocations (e.g., due towork) less distressing for the patient.

The examination unit 104 can use acquired data and processed data (e.g.,acquired data that has been processed) to create artificial intelligenceand/or machine learning with respect to dental structural and tissuechanges over time, for example, by using and/or creating one or moredatabases of acquired data and/or processed data, such as thosedescribed above. For example, the processing unit 106 can be programmedwith an algorithm and/or a cloud computing system (e.g., one or moreservers and/or networks) can be used to digest all the collected data atthe time of baseline exams and at follow-up data acquisitions (e.g.,follow-up intraoral digital data acquisitions, such as follow-up scans,x-rays, photographs). The data collected can be processed and comparedwith one or more libraries of data (e.g., databases) that arepatient-specific (i.e., data of only a single patient 101) and/ornon-patient specific (i.e., data of one or multiple people differentfrom patient 101 and/or of multiple people including patient 101) tomore accurately determine the progress of the disease, make diagnosesand predictions, and to compare functional dental deficiencies againstthe norm. In this way, artificial intelligence and machine learning candesirably allow dentists and patients alike to make more informeddecisions about the dental treatment based on the more accuratediagnoses.

One or more aspects of the system 100 can be voice and/or gesturecontrolled. For example, the examination unit 104 can be voice and/orgesture controlled via a control interface. Alternatively, or incombination, the system 100 can have a control interface such that theexamination unit 104 can be instructed to “look for”—identify, if itexists—one or more specific conditions, as opposed to performing a fullycomprehensive examination of the data acquisition results. This can beuseful, for example, where time is limited, to re-confirm the existenceof an identified condition, and/or to re-confirm the absence of acondition. It also gives medical professionals the ability to focussubsequent exams on areas that the examination unit 104 may not haveemphasized in previous or current analyses. Such a control unit canreceive input to analyze the entire dentition, a subset thereof, asingle tooth, a portion of a single tooth, one or more portions ofmultiple teeth, or any combination thereof. The control unit can be, forexample, a controllable interface, including one or more controls (e.g.,one or more multi-state controls), that can be manually or automaticallymanipulated to adjust the analysis parameters of the system 100. Theanalysis parameters can be set, for example, to identify one or multipleconditions, one or multiple reference points (should they exist), softtissue having a certain characteristic, hard tissue having a certaincharacteristic, or any combination thereof. Such certain characteristicscan include, for example, the size, shape, quantity (e.g., mass, volume,etc.), coloration, level of vascular perfusion, structure, structuralintegrity, or any combination thereof, of soft and/or hard tissue. Thecontrols can be one or more touch screens, touch surfaces, ormanipulatable mechanisms (e.g., buttons, switches, knobs, orcombinations thereof). The manipulatable mechanisms can be translatableand/or rotatable.

As described above, the examination unit 104 can quantify and/or map anydetectable (e.g., scannable, radiographable, photographable) dentalcondition. Such conditions can include dental structures, diseases, anddeficiencies (e.g., functional deficiencies). To allow for suchanalysis, the examination unit 104 can determine the location andcondition of soft and/or hard tissue, including its size, shape,quantity (e.g., mass, volume, etc.), coloration, level of vascularperfusion, structure, structural integrity, or any combination thereof.For example, the examination unit 104 can differentiate between—and canmeasure, map, or otherwise determine the extent of—plaque, enamel,dentin, pulp, gum, cement, nerves (e.g., innervation), blood vessels,bone, restorative materials, bacteria, or any combination thereof. Asanother example, the examination unit 104 can differentiate between thecrown, neck, and/or root of each tooth, and can measure, map, orotherwise determine the extent of each. The examination unit 104 canidentify the type of each tooth digitally captured (e.g., imaged via ascan, an x-ray, a photo, or any combination thereof), for example,whether the tooth is a molar, premolar, canine, or incisor. Based partlyor completely on an analysis of some or all of the above, theexamination unit 104 can diagnose the conditions a patient (e.g.,patient 101) has, if any. The examination unit 104 can also identifyhealthy tissue and highlight this for discussion with the patient, or todirectly inform the patient. The identification of healthy tissue inaddition to unhealthy tissue can provide encouraging feedback topatients, and facilitate more active participation by the patient 101 intheir own treatment.

The mappings (e.g., numeric and/or visual) can have multiple layers thatare selectable and/or have varying degrees of transparency or otherdistinguishing features (e.g., colors, color gradients, symbols, etc.).For example, the enamel and dentin layer can be selected such that theunselected features or the other selectable features are not shown onthe map. Every iteration of selectable features is hereby disclosed(i.e., anything that can be quantified and/or mapped), and is thereforeclaimable.

Acquirable (e.g., observable and/or detectable, for example, scannable,radiographable, photographable) and electronically examinable dentalstructures include, for example, attrition, abrasion, abfraction,erosion, wear, non-carious tooth substance loss, fractured teeth,fracture lines in teeth, anomalies, missing teeth, edentulous spaces,crowding and spacing of the dentition, restorations, defectiverestorations, restorative materials, caries, re-current caries, or anycombination thereof. As described below, FIGS. 2A-10 illustrate variousexemplary conditions that the system 100 can observe, detect, analyze,and electronically document, in any combination, along with exemplaryreference points for each. The various properties of reference andpotential reference points described in relation to each of FIGS. 2A-10below are applicable for any reference and potential reference point forany dental disease, condition, or deficiency, for example for any of theother conditions shown in FIGS. 2A-10. For clarity in the followingdescription, some properties have been repeated in the various Figuredescriptions, and some have not. However, and merely to reiterate theintent of the following description of FIGS. 2A-10, the inclusion ofsubject matter in the descriptions of some figures but its omission fromother figures is not an omission of that subject matter from thosefigures that do not include such descriptions.

Attrition

Attrition is the loss of tooth substance caused by physiologictooth-to-tooth contact. Attrition predominately causes wear on theincisal edges and occlusal surfaces of the teeth. One or more 2D or 3Dimages (e.g., scans, x-rays, photographs) can be used to identify orform an image of attrition. 2D images can be constructed into a 3D imageor a 3D image can be generated directly, for example using a camera, anx-ray device, or an intra-oral 3D scanner. FIGS. 2A-2E illustrate adiagrammatic representation of a variation of dental attrition 52forming over time. FIG. 2A illustrates an upper tooth U and a lowertooth L before the effects of attrition can be seen, FIG. 2E illustratesattrition 52 on the upper and lower teeth U, L, and FIGS. 2B-2Dillustrate the progression of the attrition 52 on the lower tooth L inthe span of time between the snapshots shown in FIGS. 2A and 2E.

The reference point for attrition can be the contact point or contactsurface (e.g., planar, curved, or irregularly shaped) where two or moreteeth contact one another, for example, where two occlusal surfacescontact each other, and/or where an occlusal surface of a first toothcontacts a side of a second tooth. The reference point for attrition canbe exposed dentin, for example, an exposed spot or area of dentin. Forexample, FIGS. 2A and 2E illustrate that the system 100 can determine afirst reference point 52 a and a second reference point 52 b between theupper and lower teeth U, L. The system 100 can determine the firstreference point 52 a from a first (e.g., baseline) data acquisition, andthe second reference point 52 b from a subsequent (e.g., second, third,fourth, fifth, or more) data acquisition. The system 100 can determinethe dimensions and the extent of the first and second reference points52 a, 52 b and compare them to each other. For example, the length,width, and height, as well as the size, surface area, and outline ofeach reference point (e.g., 52 a and 52 b), in any combination, can bedetermined and compared to one another. The volume of tooth loss betweenany two reference points (e.g., 52 a and 52 b) can be determined andcompared, as can a ratio between any measured dimension or derived value(e.g., surface area). The area of the surfaces that are undergoing wearcan be measured and quantified. The area of dentin exposed can bemeasured and quantified.

The first and second reference points 52 a, 52 b (also referred to asreference regions) can correspond to where contact between the upper andlower teeth U, L occurs (e.g., the one or more points or regions whereit actually occurs, and/or a boundary extending around the outermostcontact points and/or regions). The first and second reference points 52a, 52 b can correspond to where dentin has been exposed. Alternativelyor additionally, the first and second reference points 52 a, 52 b can bea reference region that includes the contact area and a region slightlybeyond the contact area. For example, a two-dimensional shape (e.g., acircle, an ellipse, a triangle, square, rectangle, pentagon, hexagon, orother polygonal shape, including a series of connected line segmentsforming a closed shape, where the line segments can be straight and/orform one or more arcs) or a three-dimensional shape (e.g., sphere,spheroid, ellipsoid, or three-, four-, five, six-, seven-, or more-sidedprism) can extend around a center of the contact area in across-sectional view and a three-dimensional view, respectively. Thetwo- or three-dimensional shape can include the contact point and anarea beyond the contact area. For example, the shape can extend at aconstant or variable distance beyond a boundary of the contact area, forexample, from about 0.1 mm to about 5.0 mm and every 0.1 mm incrementtherebetween. Using a two-dimensional shape to surround the contact areain a side or cross-sectional view and/or a three-dimensional shape tosurround the contact area in a three-dimensional view allows thereference point to be approximated. For example, FIGS. 2A and 2Eillustrate that the first and second circles 52 a, 52 b each surroundthe contact area and include a space around the contact area. The areaor volume of the first and second reference shapes (e.g., first andsecond reference circles 52 a, 52 b) can be compared to one another sothat the extent of tooth loss due to abrasion can be approximated.Although only a single side view reference point is illustrated in FIGS.2A and 2B, the system 100 can determine multiple two-dimensional side orcross-sectional reference points, and/or can determine one or multiplethree-dimensional reference points.

FIGS. 2A and 2E also illustrate that the system 100 can determine afirst potential reference point 53 a and a second potential referencepoint 53 b. The first and second potential reference points 53 a, 53 bcan be smaller or larger than the first and second reference points 52a, 52 b. For example, FIGS. 2A and 2E illustrate that the first andsecond potential reference points 53 a, 53 b can be larger than thefirst and second reference points 52 a, 52 b. The system 100 canestimate the first and second potential reference points 53 a, 53 b, forexample, based on the first and second reference points 52 a, 52 b. Thefirst and second reference points 53 a, 53 b, can be sized so that thefirst and second potential reference points 53 a, 53 b do not changebetween two adjacent data acquisitions. The first and second potentialreference points 53 a, 53 b can provide the system 100 with a referencefrom which to anchor an analysis of a subsequent data acquisition. Thefirst and second potential reference points 53 a, 53 b can have anytwo-dimensional or three-dimensional shape as described above withrespect to the first and second reference points 52 a, 52 b. The firstand second potential reference points 53 a, 53 b can have the same or adifferent shape than the first and second reference points 52 a, 52 b.The reference and potential reference points can each have the sameshape as or a different shape than another reference or potentialreference point. The system 100 can determine a potential referencepoint for every reference point that is determined.

Although not illustrated in FIGS. 2A and 2E, the reference and potentialreference points 52 a, 52 b, 53 a, 53 b can enclose or surround dentinthat has been exposed due to wear.

Tooth Wear & Non-Carious Tooth Substance Loss

Tooth wear and non-carious tooth substance loss refers to the loss oftooth substance by means other than dental caries or trauma. One or more2D or 3D images (e.g., scans, x-rays, photographs) can be used toidentify or form an image of attrition. 2D images can be constructedinto a 3D image or a 3D image can be generated directly, for exampleusing a camera, an x-ray device, or an intra-oral 3D scanner. FIG. 3illustrates a diagrammatic representation of two cross-sectional andocclusal views of a variation of a first and a second tooth 50 a, 50 bwith wear 57 extending into the enamel 58 and dentin 59. A portion ofthe dentin 59 is shown exposed on the occlusal surfaces.

The reference point for tooth wear and non-carious tooth substance losscan be the contact point or contact surface where two or more teethcontact one another, for example, where two occlusal surfaces contacteach other, or where an occlusal surface of a first tooth contacts aside of a second tooth. The reference point for tooth wear andnon-carious tooth substance loss can be exposed dentin, for example, anexposed surface of dentin. For example, FIG. 3 illustrates that thesystem 100 can determine a first side view reference point 57 a and afirst occlusal view reference point 57 b for the first tooth 50 a, andcan determine first and second side view reference points 57 c, 57 d andfirst and second occlusal view reference points 57 e, 57 f for thesecond tooth 50 b. The system 100 can determine the various referencepoints 57 a-57 f on the first and second teeth 50 a, 50 b from a firstdata acquisition (e.g., a baseline or subsequent data acquisition). Thesystem 100 can determine the dimensions and the extent of the variousreference points 57 a-57 f on the first and second teeth 50 a, 50 b andcompare them to subsequent reference points determined from one or moresubsequent data acquisitions. For example, the length, width, andheight, as well as the size, surface area, and outline of each referencepoint (e.g., 57 a-57 f), in any combination, can be determined andcompared to one another. The volume of tooth loss between the determinedreference points (e.g., 57 a-57 f) and reference points determined froma subsequent data acquisition can be determined and compared, as can aratio between any measured dimension or derived value (e.g., surfacearea). The area of the surface that is undergoing wear can be measuredand quantified. The area of dentin exposed can be measured andquantified.

FIG. 3 illustrates that the system 100 can determine a reference pointfor each tooth individually. The various reference points 57 a-57 f cancorrespond to where the first and second teeth 50 a, 50 b contactanother tooth (not shown). The various reference points 57 a-57 f cancorrespond to where dentin has been exposed. Alternatively oradditionally, the various reference points 57 a-57 f can correspond to aboundary extending around the outermost contact points and/or regions,for example, such that the reference points 57 a-57 f comprise areference region that includes a contact area and a region slightlybeyond the contact area. The various reference points 57 a-57 f can havea two-dimensional and/or a three-dimensional shape as described abovewith reference to FIGS. 2A and 2E. For example, FIG. 3 illustrates thatthe various reference points 57 a-57 f can each have an irregularpolygonal shape, and/or a non-angular shape (e.g., circular shape,elliptical shape, hemispherical). Although not shown, the area or volumeof the various reference points 57 a-57 f (e.g., the various referenceshapes 57 a-570 can be compared to one another so that the extent oftooth loss due to abrasion can be approximated. Although only a singleside and occlusal view reference point is illustrated for each of thefirst and second teeth 50 a, 50 b in FIG. 3 for each area of abrasionshown, the system 100 can determine multiple two-dimensional side orcross-sectional reference points, and/or can determine one or multiplethree-dimensional reference points.

FIG. 3 also illustrates that the system 100 can determine a first sideview potential reference point 57 a′ and a first occlusal view potentialreference point 57 b′ for the first tooth 50 a, and can determine firstand second side view potential reference points 57 c′, 57 d′ and firstand second occlusal view potential reference points 57 e′, 57 f′ for thesecond tooth 50 b. The potential reference points illustrated in FIG. 3can have the same properties as the potential reference points describedabove with reference to FIGS. 2A and 2E.

Although not illustrated in FIG. 3, the reference and potentialreference points 57 a-57 f and 57 a′-57 f ‘ can enclose or surrounddentin that has been exposed due to wear.

Erosion

Erosion is the chemical dissolution of tooth substance caused by acidsunrelated to the acids produced by bacteria in dental plaque. Erosioncan occur with excessive consumption of acidic foods and drinks, ormedical conditions involving the repeated regurgitation and reflux ofgastric acid. Erosion on a tooth can present as one or more discoloredregions that have a different shade as compared to non-eroded portionsof the tooth/teeth. For example, the eroded portion of a tooth can begrey, including light grey to dark grey. Erosion can be captured using ascanner, for example a computed tomography (CT) scanner (e.g., a CBCTscanner). FIG. 4 illustrates a diagrammatic representation of avariation of chemical erosion 56 of a tooth. FIG. 4 illustrates that thesystem 100 can identify or otherwise determine a reference point 56 aand a potential reference point 56 a’. The system 100 can determine thereference and potential reference points 56 a, 56 a′ based on the color(e.g., shade) of one or more portions of the tooth. For example, theshade of the reference regions 56 a, 56 a′ can include a shade of colorthat is darker (or lighter) than the portion of the tooth not includedin the reference regions 56 a, 56 a′. The area of erosion can be thedarker and/or lighter portions of the teeth. FIG. 4 further illustratesthat the reference points (e.g., reference points 56 a, 56 a′) can havean irregular curved shape comprised one or more curved line segments.The system 100 can use a shade detection device (e.g., an electronictooth shading ruler, a camera) to calibrate the detected shades so thatthe detected shades can be compared to one another over time, forexample from different a first and a subsequent data acquisition.

Abrasion & Abfraction

Abrasion is the loss of tooth substance caused by physical means otherthan teeth (i.e., other than by physiologic tooth-to-tooth contact).Abrasion tends to present as rounded ditching around the cervicalmargins of teeth, commonly described as shallow, concave or wedge shapednotches. Abrasion can be caused by improper use of a toothbrush, dentalfloss or toothpicks. Abfraction is similar to abrasion but is caused bybruxing (i.e., grinding) or clenching of the teeth. Bruxing/clenchingcauses enough stress at the cervical margin to create wedge shapeddeficits. One or more 2D or 3D images (e.g., scans, x-rays, photographs)can be used to identify or form an image of abrasion and abfraction. 2Dimages can be constructed into a 3D image or a 3D image can be generateddirectly, for example using a camera, an x-ray device, or an intra-oral3D scanner. The gum attachment point 54 a to the tooth 55 a can becaptured using a scanner, for example a computed tomography (CT) scanner(e.g., a CBCT scanner). The images of a CBCT scanner and a radiographcan be combined to quantify and/or map abrasion and abfraction where thegum attachment point to a tooth is being tracked. FIG. 5 illustrates adiagrammatic representation of a variation of abfraction and/or abrasion54 at the cervical margin of a tooth. FIG. 5 illustrates where the gum55 a contacts the tooth 55 b.

The reference point for abrasion and abfraction can be the contact pointor contact surface where two or more teeth contact one another, forexample, where two occlusal surfaces contact each other, or where anocclusal surface of a first tooth contacts a side of a second tooth. Thereference point for abrasion and abfraction can be a surface notch,ditch, divot, or indentation on a tooth surface, for example, on a sideof the tooth, on an occlusal surface, and/or on the ridge marking theboundary between a side tooth surface and an occlusal surface. Thereference point for abrasion and abfraction can be exposed dentin, forexample, an exposed surface of dentin. The reference point for abrasionand abfraction can be the contact point between the gum and a tooth.

For example, FIG. 5 illustrates that the system 100 can determine afirst reference point 54 a and a first potential reference point 54 a′.The reference points 54 a and 54 a′ can be a gum-tooth contact location(i.e., potential contact locations for the potential reference point 54a′), and can correspond to a lower (or upper) extent of a roundedditching around a cervical margin of a lower tooth (or upper tooth).FIG. 5 further illustrates that the reference and potential referencepoints (e.g., reference points 54 a and 54 a′) do not need to beconcentric with one another. FIG. 5 further illustrates that theboundary of a potential reference point can overlap with a center of athe actual reference point, for example for the possible observableevent in which the gum contact point remains at the same location in asubsequent data acquisition, and does not further deteriorate (by movingdownward on the page of FIG. 5 along the tooth surface), and does notimprove (by moving upward on the page of FIG. 5 along the toothsurface).

Fractures & Fracture Lines

Fractured teeth are missing part of if not all the clinical crown of thetooth below or above the gum line. Fracture surfaces can present as oneor more discolored regions, and can change the boundary of teeth to aboundary outside of physiological norms. Fracture lines are withinintact teeth/tooth structures and indicate that the tooth/teeth areweakening. Fracture lines generally cannot be visually monitored overtime using traditional manual visual inspection and examination methods.Fracture lines can present as one or more discolored regions or linesthat have a different shade as compared to non-fractured portions of thetooth/teeth. For example, a fracture line of a tooth can be grey,including light grey to dark grey. Fractures (e.g., fracture surfaces)and fracture lines can be captured using a camera and/or an x-raydevice, as well as a color detection device as described above withreference to FIG. 4. For example, the system 100 can use a shadedetection device (e.g., an electronic tooth shading ruler, a camera) tocalibrate the detected shades so that the detected shades can becompared to one another over time, for example from different a firstand a subsequent data acquisition. FIG. 6 illustrates a diagrammaticrepresentation of a variation of a fractured tooth having a fracturedportion 62 that has broken away from the tooth and a variation of atooth having a fracture line 64. FIG. 6 illustrates that the system 100can identify or otherwise determine a reference point 62 a and apotential reference point 62 a′ corresponding to a fracture surface, andcan identify or otherwise determine a reference point 64 a and apotential reference point 64 a′ corresponding to a fracture line. Thesystem 100 can determine the reference and potential reference points 62a, 62 a′, 64 a, 64 a′ based on the color (e.g., shade) of one or moreportions of the tooth. For example, the shade of the reference regions62 a, 62 a′, 64 a, 64 a′ can include a shade of color that is darker (orlighter) than the portion of the tooth not included in the referenceregions 62 a, 62 a′, 64 a, 64 a′. The fracture surface and fracture linecan be the darker and/or lighter portions of the teeth.

Tooth Anomalies

Anomalies of the teeth can include, for example, supernumerary teeth,hyperdontia, hypodontia, fusion, germination, macrodontia, microdontia,or any combination thereof. FIG. 7 illustrates a diagrammaticrepresentation of a normal sized tooth 60, microdontia 66, supernumeraryteeth 67 and a fusion of teeth 68. One or more 2D or 3D images (e.g.,scans, x-rays, photographs) can be used to identify or form an image ofsuch anomalies. 2D images can be constructed into a 3D image or a 3Dimage can be generated directly, for example using a camera, an x-raydevice, or an intra-oral 3D scanner. The system 100 can determine thetype of teeth (e.g., molar, premolar, canine, or incisor) imaged orotherwise under digital evaluation. The system 100 can identify orotherwise determine a reference point for each tooth, with eachreference point corresponding to the size of the tooth, or arepresentative size of the tooth. For example, FIG. 7 illustrates thatthe system 100 can determine reference points 60 a, 66 a, 67 a, and 68 afor teeth 60, 66, 67 and 68, respectively.

The size of the reference points (e.g., 60 a, 66 a, 67 a, and 68 a) canbe the actual size or an approximate size of a tooth. For example, FIG.7 illustrates that the references points 60 a, 66 a, 67 a, and 68 a canbe approximated with squares and rectangles; however, any curved orangular 2D shape (e.g., circles, ellipses, and polygons) or 3D shape(e.g., spheres, spheroids, ellipsoids, hemispheroids, and prisms) isappreciated. The reference points can be measured in any side view,occlusal view, 3D view, or can be construction of one or more views. Forexample, FIG. 7 illustrates that the references points 60 a, 66 a, 67 a,and 68 a can be side view reference points.

The size of each reference point can be the volume of the tooth, thetotal surface area of the tooth (e.g., above the gum line), the surfacearea of an occlusal surface of the tooth, the surface area of one ormore sides of the tooth, the surface area of a portion of any of thesemeasured surface areas, or any combination thereof. When multiple teethare imaged, the same or different reference point measurement can beused on each tooth. Further, multiple reference point measurements canbe performed on the same tooth and then averaged.

The reference points (e.g., 60 a, 66 a, 67 a, and 68 a) can be thesurface area of one or more sides of each of the teeth 60, 66, 67 and68, and/or the occlusal surface of each of the teeth 60, 66, 67 and 68.The surface area in the squares and rectangles 60 a, 66 a, 67 a, and 68a can account for the curvature of the teeth within the squares andrectangles 60 a, 66 a, 67 a, and 68 a (e.g., at the corners of theteeth, and/or along the faces of the teeth), or the surface area in thesquares or rectangles 60 a, 66 a, 67 a, and 68 a can ignore or notmeasure the surface area attributable to curvature of a tooth surface.Alternatively or additionally, the areas of the squares and rectangles60 a, 66 a, 67 a, and 68 a can be used to approximate the size of theteeth. Although not shown, the geometric shape positioned over the teeth(e.g., the squares and rectangles 60 a, 66 a, 67 a, and 68 a) can beselected such that the tooth is entirely within the geometric shape, andsuch that each side of the geometric shape has a location that is 1 mmor closer to a surface of the tooth.

The system 100 can calibrate the sizes of the teeth against a databaseof sizes, for example by selecting one or more normal sized teeth andcomparing the selected teeth to the teeth sizes in the database. Thesizes in the database can be acquired from the teeth of other patientsand/or can be theoretical teeth sizes, where teeth are compared to otherlike teeth, not other similar teeth, such that each tooth in a dentitionis compared to a tooth in the exact same position as measured in anotherpatient or modeled in a theoretically sized dentition. The sizes in thedatabase can be acquired from other similar teeth of the patient, othersimilar teeth of other patients and/or can be theoretical teeth sizes ofother similar teeth, where “other similar teeth” means that molars arecompared to molars, premolars are compared to premolars, canines arecompared to canines, and incisors are compared to incisors, includingeither teeth in the same position or a different position. For example,the reference points 60 a, 66 a, 67 a, and 68 a can be compared to thedatabase sizes (i.e., sizes of other similar teeth of the patient, sizesof the same or one or more other similar teeth of one or more otherpatients, or theoretical sizes of the tooth or other similar teeth).Alternatively or additionally, the system 100 can have a database with athreshold size for each tooth. The system 100 can compare the referencepoints 60 a, 66 a, 67 a, and 68 a to the respective threshold sizes. Bycomparing reference points (e.g., reference points 60 a, 66 a, 67 a, and68 a) to one or more database sizes and/or one or more referencethresholds, the system 100 can determine whether a dentition comprisessupernumerary teeth, hyperdontia, hypodontia, fusion, germination,macrodontia, microdontia, or any combination thereof. For example, FIG.7 illustrates that the system 100 can identify microdontia 66 where thereference point (e.g., 66 a) has a size that is less than a databasesize and/or a threshold size. The system 100 can identify supernumeraryteeth 67 where the reference point (e.g., 67 a) has a size that is lessthan a database size and/or a threshold size. The system 100 canidentify tooth fusion 68 where the reference point (e.g., 68 a) has asize that is greater than a database size and/or a threshold size.

Missing Teeth & Edentulous Spaces

Missing teeth and edentulous spaces can affect masticatory efficiencyand cause structural shifts and are therefore desirable to document.FIG. 8 illustrates a diagrammatic representation of a variation of amissing tooth and an edentulous space 72. One or more 2D or 3D images(e.g., scans, x-rays, photographs) can be used to identify or form animage missing teeth and edentulous spaces 72. 2D images can beconstructed into a 3D image or a 3D image can be generated directly, forexample using a camera, an x-ray device, or an intra-oral 3D scanner. Acomputed tomography (CT) scanner (e.g., a CBCT scanner) can be used tocapture gaps between teeth. For example, a 3D intra-oral scanner and anx-ray device can be used to determine the presence of an edentulousspace 72 where a baby tooth is under (e.g., still under) the gum.

FIG. 8 illustrates that the system 100 can determine the gap, if any,between adjacent teeth. For example, the system 100 can determine areference point between adjacent teeth that corresponds to a gap, ifany, between the adjacent teeth. For example, FIG. 8 illustrates thatthe system 100 can determine a first and/or a second reference point 72a, 72 b, where each reference point can quantify the size of the gap(e.g., edentulous space) 72 between a first tooth and a second tooth(e.g., first and second teeth 71 a, 71 b). The first reference point 72a can be the size (e.g., length, width) of the gap 72 as measured fromthe two closest points of the first and second teeth 71 a, 71 b. Thesecond reference point 72 b can be the size (e.g., length, width) of thegap 72 as measured from the center, or an approximate center, of thefirst and second teeth 71 a, 71 b. The system 100 can compare thedimensions 71 a and/or 71 b to a threshold gap dimension, where thethreshold gap dimension can be from about 1 mm to about 10 mm, includingevery 1 mm increment therebetween. The system 100 can indicate thepresence of a gap (e.g., edentulous space) where the first and/or seconddimensions 71 a, 71 b matches or exceeds the threshold gap dimension.

Restorations, Defective Restorations & Restorative Materials

Restorations, defective restorations, and restorative materials aredesirable to electronically document as well. Caries and re-currentcaries around existing dental restorations is the demineralization andbacterial invasion of the tooth structures. Restorations on a tooth canpresent as one or more discolored regions that have a different shade ascompared to non-eroded portions of the tooth/teeth. For example, therestored portion of a tooth can be grey, including light grey to darkgrey when digitally acquired, for example with an x-ray device or ascanner (e.g., a computed tomography (CT) scanner or cone beam CT (CBCT)scanner). FIGS. 9A-9D illustrate diagrammatic representations ofvariations of different restorative materials 74 for dentalrestorations, demineralization, decay and re-current decay. FIGS. 9A-9Dillustrate that the system 100 can identify or otherwise determinereference points 74 a, 74 b, 74 c, and 74 d that can be tracked overtime in one or more subsequent data acquisitions after an initial dataacquisition, for example to determine the occurrence and extent ofdemineralization, decay and re-current decay. Using such imagingtechniques, the system 100 can identify the discoloration caused byrestorative material, including restorative material made of a materialthat has the same color as teeth when viewed by the naked eye, but adifferent color when captured by an x-ray device or CT (e.g., CBCT)scanner. FIG. 9A further illustrates that the reference and potentialreference points disclosed herein can be separated into one or moresub-regions, for example, 8 sub-regions as shown for reference point 74a. FIG. 9B further illustrates that the reference and potentialreference points disclosed herein can have one or more overlappingregions, for example, 1 overlapping region as shown for reference point74 b. FIG. 9D further illustrates that multiple reference and potentialreference points can be identified on a single tooth, for example, 3separate reference points as shown for reference point 74 d.

Periodontal Structures

Acquirable and electronically examinable periodontal structures include,for example, gingival recession or the pulling away of the gums from theteeth, the gingival margin, the free gingival margin, the mucogingivalline, minimal attached tissue, furcation, or any combination thereof.

The gingival margin is the position of the free gingival margin inrelation to the cervical enamel junction of the tooth. The free gingivalmargin is the interface between the sulcular epithelium and theepithelium of the oral cavity. The mucogingival line is the delineationof the attached gingival and the mucosa. Furcations represent a level ofrecession and bone loss that expose the junction of the root formationsof posterior teeth. FIG. 10 illustrates a diagrammatic representation ofvarious periodontal structures including the gingival margin (GM) 82,furcation 84, mucogingival line (MGL) 86, recession 88, and minimallyattached tissue (MAT) 90. The size and extent of these features canrepresent reference points that the system 100 can identify and quantifyso that they can each be tracked over time in one or more subsequentdata acquisitions after an initial data acquisition.

Although not illustrated in FIGS. 2A-10, the system 100 can mark healthyportions of a dentition with one or more reference points as well, toindicate that one or more portions of a tooth or multiple teeth arecurrently unaffected by deterioration or deficiency. This can make theemergence of dental conditions, diseases, and/or deficiencies easier totrack.

As described above, the data acquisition device 102 can record thestructure and extent of these features. The processing unit 104 can“examine” data acquisition data by analyzing it such that the variousillustrated and non-illustrated features can be quantified and mapped.

Method of Use

FIG. 11 illustrates a variation of a process 200 that is implementableusing and/or performable by the system 100. The method 200 can involveacquiring (e.g., detecting and/or observing, for example, scanning,x-raying, photographing) oral features with one or more data acquisitiondevices 102 in operation 202. The data acquisition in operation 202 canbe an initial baseline data acquisition, any subsequent data acquisition(e.g., a data acquisition after the baseline data acquisition or anyother data acquisition), or any standalone data acquisition unrelated toany previous or future data acquisition.

The method 200 can further involve electronically detecting one or moreoral features in a data acquisition (e.g., one or more images acquiredvia a scan, an x-ray, a photograph, or any combination thereof) of oneor multiple patients (e.g., patient 101) in operation 204. The featurescan be detected as described herein, for example, by identifyinganatomical markers and/or patterns (e.g., peaks, valleys, geometries,shapes, lines, perimeters, outlines, or any combination thereof), therelative positions of soft and/or hard tissues to another soft and/orhard tissue (e.g., the relative positions of one or more anatomicalmarkers to one or more other of the same or different anatomicalmarkers), light absorption, light reflection, colors (e.g., hues),tints, tones, and shades of colors (e.g., light, medium, and/or darkshades of a hue), changes in any of the foregoing, or any combinationthereof. The features detected can be one or more reference points, orthe reference points can be derived from one or more of the featuresdetected (e.g., from the raw data associated with a data acquisition).

The method 200 can further involve digitally analyzing/assessing thedetected features in operation 206, for example, by quantifying (e.g.,measuring) and/or mapping the features that are detected with theprocessing unit 106. Although not shown in FIG. 11, operations 204 and206 can be reversed such that the hard and/or soft tissues associatedwith the masticatory system can first be quantified and/or mapped byanalyzing the acquired data, after which the oral features can bedetected from and/or by analyzing the quantifications and/or mappings.Also not shown in FIG. 11, operation 204 can be omitted altogether suchthat the oral features can be quantified and/or mapped without anyassociated (e.g., preceding, concurrent, or subsequent) detectionanalysis, or can be combined with operation 206 such that thequantification and/or mapping of the acquired data is the detection oforal features, i.e., the features that are quantified and/or mapped arethe features detected.

The method 200 can further involve analyzing the quantifications and/ormappings in operation 208. For example, the processing unit 106 can usethe quantifications and/or mappings to estimate the extent of theexisting conditions, make diagnoses and/or prognoses, determine whetherto treat or monitor the existing conditions, determine whether topreventatively treat not yet manifested conditions, recommend one ormore treatments and/or treatment regimes, develop educational plans, orany combination thereof, as described in more detail above in relationto the system 100. FIG. 11 illustrates, for example, a diagnosisdecision in operation 208-1 and a determination to treat or monitor thediagnoses in operation 208-2.

The method 200 can further involve comparing the acquired data, detectedfeatures, and/or analyses (e.g., quantifications, and/or mappings) topreviously obtained data acquisitions and/or data acquisition analysesin operation 210. In addition to or in lieu of operations 208-1 and208-2, FIG. 11 illustrates that these operations can occur in operations210-1 and 210-2 such that the comparison operation 210 can be, but neednot be, informative or otherwise a contributing factor in the diagnose,treatment, and/or monitor determinations in operations 210-1 and 210-2.

The method 200 can further involve electronically storing any of thedata associated with and/or derived from the operations described inthis disclosure, for example, those shown in method 200, includingoperations 202, 204, 206, 208, 208-1, 208-2, 210, 210-1, 210-2 (e.g., indata logs or other data representative of stored data), and/or any dataand/or analyses associated with a reacquisition of data (e.g., a rescan,a second or subsequent x-ray, a second or subsequent photograph) of oralfeatures in operation 212.

The method 200 can further involve reacquiring (e.g., rescanning,re-x-raying, re-photographing) oral features of a patient (e.g., patient101) in operation 214 and repeating and performing operations 202, 204,206, 208, 208-1, 208-2, 210, 210-1, 210-2, 212, 214, or any combinationthereof.

The operations 202, 204, 206, 208, 208-1, 208-2, 210, 210-1, 210-2, 212,214 can be interchangeably combined, rearranged, substituted, and/oromitted in any combination, and can be executed in any order, forexample, in the order shown. Additional operations that are not showncan be added to the method 200 or can be part of a separateimplementable and/or performable method, for example, making prognoses,predicting the manifestation of not yet manifested conditions,identifying causal variables (e.g., physiological, psychological,bacterial, and/or environmental variables), generating treatment plans,making recommendations regarding treatment and monitoring, or anycombination thereof, as well as any other process or operation describedor contemplated herein.

FIG. 12 illustrates a variation of an algorithm 300 executable by thesystem 100, for example, by the processing unit 106, a cloud server,software spread over a network, or any combination thereof, in additionto any other processing protocol described and contemplated herein. Thealgorithm 300 can be executable code stored in the memory unit 108 or inan external memory, for example, on a server.

The algorithm 300 can start in operation 302. Upon starting, thealgorithm 300 can involve receiving data associated with a dataacquisition, for example, data from one or multiple data acquisitionscarried out in operation 202. Alternatively, or in combination, thealgorithm 300 can start automatically upon receiving acquired data inoperation 304.

The algorithm 300 can further involve processing acquired data inoperation 306. For example, FIG. 12 illustrates that the processing unit106 can perform operations 204, 206, 208, or any combination thereof.Features can be detected in operation 204. The detected features can bequantified (e.g., measured) and/or mapped in operation 206. In operation208 the quantifications and/or mappings can be analyzed. As describedabove with reference to FIG. 11, operations 204, 206, and 208 can beinterchangeably combined, rearranged, substituted, and/or omitted toachieve the exact data processing flow desired; they are each againshown here to illustrate a variation of a process flow that theprocessing unit of the system 100 can implement or otherwise execute inthe form of an exemplary executable algorithm. Operation 209 shows thatthe extent of the quantified (e.g., measured) and/or mapped features canbe estimated, for example, by analyzing the quantifications and mappingsand linking or otherwise tying this analysis to the digitally captured(e.g., imaged via a scan, an x-ray, a photo, or any combination thereof)soft and/or hard tissue structures, diseases, and/or deficiencies. Forexample, operation 209 can be executed if a threshold condition inoperation 208 is satisfied, for example, if a ratio of one or moreaspects of a tissue or tissue feature satisfies or exceeds a thresholdratio.

The algorithm 300 can further involve performing statistical analysis onthe data generated in operation 306 and/or on the raw acquired datareceived in operation 304. The processing unit 106 can compare theprocessed results to one or more statistical variables (e.g.,qualitative and/or quantitative variables) or any other benchmark value,to previous results, and/or to one or more libraries of data indatabases (e.g., corresponding to data from one or multiple people). Forexample, the data in operation 210 can be compared to statistical valuessuch as norms, averages, maximums, minimums, standard deviations,ratios, or any combination thereof. As shown in FIG. 12, processedand/or raw data can be compared to norms, result databases, and/or topreviously obtained data acquisition results (e.g., raw and/or analyzedacquisition data) in operation 210. The algorithm 300 can, for example,further involve retrieving or otherwise referencing data from a resultdatabase (e.g., from memory unit 108 and/or external database 112) inoperation 307 and/or can involve retrieving or otherwise referencingpreviously obtained data acquisition results from the same patientand/or one or multiple different patients (e.g., stored in memory unit108 and/or external database 112) in operation 307. FIG. 12 illustratesthat data can be retrieved in operation 307 during any processing stepin operation 306, for example, in operation 204, 206, 208, and/or 209.Further, operation 210 can be performed within or part of operation 306even though operation 210 is illustrated separate from operation 306.

The algorithm 300 can further involve determining whether to generate adiagnosis in operation 308. For example, if a processed result isgreater than or equal to a diagnosis threshold, the algorithm 300 caninvolve generating one or more diagnoses in operation 312. If theprocessed result is less than the diagnosis threshold, the algorithm 300can involve not generating a diagnosis and/or indicating that there arecurrently no existing conditions related to the processed result inoperation 310.

The algorithm 300 can further involve determining, for each generateddiagnosis (e.g., in operation 312), whether to treat or monitor thecondition or conditions associated with each generated diagnosis. Forexample, if a diagnosis value is greater than or equal to a treatmentthreshold, the algorithm 300 can involve making a recommendation totreat the diagnosed conditions in operation 316. If the diagnosis valueis less than the treatment threshold, the algorithm 300 can involvemaking a recommendation to monitor the diagnosed conditions in operation318.

The algorithm 300 can further involve determining whether to make arecommendation to reacquire data (e.g., rescan, re-x-ray, re-photograph)of the patient (e.g., patient 101) in operation 320. For example,operation 320 shows that if an elapsed time is greater than or equal tothe monitoring period and/or treatment period, the algorithm 300 caninvolve making a recommendation to reacquire data of the patient, returnto operation 304 and receive the reacquisition data associated with thedata reacquisition. If the elapsed time is less than the monitoringperiod and/or treatment period, the algorithm 300 can end in operation322 or can involve indicating that it is not yet time to reacquire dataof the patient and then end in operation 322. Although not shown inoperation 320, the algorithm 300 can make a recommendation of whether toreacquire data of a patient (e.g., patient 101) based on one or moreerror thresholds or error indicators. Errors can be determined for theacquired data, reacquired data, processed data, and/or analyzed data,including the quantifications and/or mappings thereof. If a calculatedor determined error is greater than or equal to a threshold error, thealgorithm 300 can involve making a recommendation to reacquire data ofthe patient, return to operation 304 and receive the acquired dataassociated with the reacquisition. The data reacquisition can involve acomprehensive acquisition or can involve a focused acquisition thatconcentrates on the areas or conditions associated with the error. Ifthe calculated or determined error is less than the threshold error, thealgorithm 300 can end in operation 322 and/or determine whether anelapsed time is greater than or equal to the monitoring period and/ortreatment period as described above.

FIG. 13 illustrates a variation of a process 400 that is implementableusing and/or performable by the system 100. The process 400 can be analgorithm 400 executable by the system 100, for example, by theprocessing unit 106, a cloud server, software spread over a network, orany combination thereof, in addition to any other processing protocoldescribed and contemplated herein. The algorithm 400 can be executablecode stored in the memory unit 108 or in an external memory, forexample, on a server.

The method 400 can involve acquiring (e.g., detecting and/or observing,for example, scanning, x-raying, photographing) oral features with oneor more data acquisition devices 102 in operation 202. The dataacquisition in operation 202 can be an initial baseline dataacquisition, any subsequent data acquisition (e.g., a data acquisitionafter the baseline data acquisition or any other data acquisition), orany standalone data acquisition unrelated to any previous or future dataacquisition. For example, FIG. 13 illustrates that operation 202 caninvolve acquiring one or more first oral features that can correspond toa baseline data acquisition.

The method 400 can further involve electronically detecting one or moreoral features in a data acquisition (e.g., one or more images acquiredvia a scan, an x-ray, a photograph, or any combination thereof) of oneor multiple patients (e.g., patient 101) in operation 204 as describedabove with reference to method 200.

The method 400 can further involve digitally analyzing/assessing thedetected features in operation 206, for example, by quantifying (e.g.,measuring) and/or mapping the detected first oral features. Although notshown in FIG. 13, operations 204 and 206 can be reversed such that thehard and/or soft tissues associated with the masticatory system canfirst be quantified and/or mapped by analyzing the acquired data, afterwhich the oral features can be detected from and/or by analyzing thequantifications and/or mappings. Also not shown in FIG. 13, operation204 can be omitted altogether such that the oral features can bequantified and/or mapped without any associated (e.g., preceding,concurrent, or subsequent) detection analysis, or can be combined withoperation 206 such that the quantification and/or mapping of theacquired data is the detection of oral features, i.e., the features thatare quantified and/or mapped are the features detected

FIG. 13 illustrates that the first oral features can be quantifiedand/or mapped by determining one or more first (also referred to asbaseline) reference regions in operation 206. Each type of dentalcondition can have one or more reference regions associated with it. Forexample, FIGS. 2A-10 illustrate variations of various reference regionsthat the system 100 can identify, quantify, and map. Although notillustrated in operation 206, one or more first (also referred to asbaseline) potential reference regions can be determined in operation 206as well. As described above, the reference regions can be derived fromthe potential reference regions, or vice versa.

Based on the reference regions quantified and/or mapped in operation206, the processing unit 106 can estimate the extent of the existingconditions, make diagnoses and/or prognoses, determine whether to treator monitor the existing conditions (e.g., the conditions detected),determine whether to preventatively treat not yet manifested conditions,recommend one or more treatments and/or treatment regimes, developeducational plans, or any combination thereof, as described in moredetail herein in relation to the system 100. FIG. 13 illustrates, forexample, that the method 400 can involve diagnosing (or otherwiseidentifying) the first oral features in operation 208-1, for example,based partly or completely on the reference regions quantified and/ormapped in operation 206, and can involve determining whether to treat ormonitor the diagnosed first conditions in operation 208-2.

The method 400 can further involve operation 402, which can involveperforming (e.g., repeating, or performing for the first time)operations 202, 204, and/or 206 for one or more second (also referred toas one or more subsequent) oral features. Operation 402 can involveperforming operations 202, 204, and/or 206 for the first time where thefirst oral features were input manually into the system 100, forexample, after an in-person review of a dental record, electronic orphysical. Although not illustrated in operation 402, one or moresecond/subsequent potential reference regions can be determined inoperation 402 as well. From operation 402, FIG. 13 illustrates that themethod 400 can involve diagnosing (or otherwise identifying) the secondoral features in operation 402-1, for example, based partly orcompletely on the reference regions quantified and/or mapped inoperation 402, and can involve determining whether to treat or monitorthe diagnosed second conditions in operation 402-2.

The method 400 can further involve determining the progression of thereference regions over time in operation 404. For example, operation 404can involve performing operations 208, 210, and/or 212 as describedabove with reference to method 200. As shown in FIG. 13, operation 404can involve comparing one or more first/baseline reference regions toone or more second/subsequent reference regions, for example, bydetermining the discrepancy (also referred to as a change) between afirst/baseline reference region and a second/subsequent referenceregion. The determined change can be numeric (e.g., difference betweentwo values) and/or graphical in nature (e.g., a darker or lighter color,and/or representation showing improvement or decay, for example, on agraph).

The method 400 can further involve determining whether to modify,maintain, and/or terminate one or more of the treatments associated withone or more of the first conditions in operation 211. The method 400 canfurther involve whether to add or start one or more new treatments inoperation 211. The determinations in operation 211 can be based partlyor completely on the comparison between one or more first and secondreference regions in operation 404, the second conditions diagnosed inoperation 402-1, and/or the second conditions determined to be treatedin operation 402-2.

The treatment of a condition can be modified or maintained where thecondition as measured by the second data acquisition is worse than thatas measured by the first data acquisition. Oral features can bedetermined to be worse in a second condition than in a first conditionwhere, for example, one or more parameters of the reference region haveincreased or decreased (e.g., the size, surface area, length, width,height or extent has increased or decreased), a color of the referenceregion has become darker, a color of the reference region has becomelighter, blood perfusion in the reference region has increased, bloodperfusion in the reference region has decreased), and/or where the rateof disease or deficiency progression exceeds a threshold rate of change.

The treatment of a condition can be modified or maintained where thecondition as measured by the second data acquisition is better than thatas measured by the first data acquisition. Oral features can bedetermined to be better in a second condition than in a first conditionwhere, for example, one or more parameters of the reference region haveincreased or decreased (e.g., the size, surface area, length, width,height or extent has increased or decreased), a color of the referenceregion has become darker, a color of the reference region has becomelighter, blood perfusion in the reference region has increased, bloodperfusion in the reference region has decreased), and/or where the rateof disease or deficiency progression exceeds a threshold rate of change.

New treatments can be initiated, for example, where the second dataacquisition in operation 402 yields one or more newly detected dentalconditions. New dental conditions can be detected in operation 402where, for example, the conditions had not yet manifested, or wereotherwise yet undetectable, in operations 202, 204, and/or 206.

The method 400 can further involve electronically storing any of thedata associated with and/or derived from the operations described inthis disclosure, for example, those shown and referred to in relation tomethod 400, including operations 202, 204, 206, 208, 208-1, 208-2, 210,211, 402, 402-1, 402-2, 404 (e.g., in data logs or other datarepresentative of stored data), and/or any data and/or analysesassociated with a reacquisition of data (e.g., a rescan, a second orsubsequent x-ray, a second or subsequent photograph).

The method 400 can further involve reacquiring (e.g., rescanning,re-x-raying, re-photographing) oral features of a patient (e.g., patient101) and repeating and performing the operations shown and referred toin relation to method 400, including operations 202, 204, 206, 208,208-1, 208-2, 210, 211, 402, 402-1, 402-2, 404, or any combinationthereof. For example, arrows 406 in FIG. 13 illustrate that the method400 can flow from operations 211 and/or 404 to operation 402.

The operations shown and referred to in relation to method 400 can beinterchangeably combined, rearranged, substituted, and/or omitted in anycombination, and can be executed in any order, for example, in the ordershown. Additional operations that are not shown can be added to themethod 400 or can be part of a separate implementable and/or performablemethod, for example, making prognoses, predicting the manifestation ofnot yet manifested conditions, identifying causal variables (e.g.,physiological, psychological, bacterial, and/or environmentalvariables), generating treatment plans, making recommendations regardingtreatment and monitoring, or any combination thereof, as well as anyother process or operation described or contemplated herein.

FIG. 14 illustrates a variation of an algorithm 500 that the system 100can implement to observe, detect, analyze, and electronically documentdental conditions, diseases and deficiencies, for example, the dentalconditions, diseases and deficiencies shown and described with referenceto FIGS. 2A-10.

The algorithm 500 can be executable by the system 100, for example, bythe processing unit 106, a cloud server, software spread over a network,or any combination thereof, in addition to any other processing protocoldescribed and contemplated herein. The algorithm 500 can be executablecode stored in the memory unit 108 or in an external memory, forexample, on a server.

The algorithm 500 can involve operations 202 and 204 as described above,for example, with reference to the methods and algorithms illustrated inFIGS. 11-13.

The algorithm 500 can further involve determining one or more referencepoints/regions associated with one or more detected oral features inoperation 502, for example, one or more detected dental conditions,diseases, and/or deficiencies. Although not illustrated in operation502, one or more potential reference regions can be determined inoperation 502 as well. As described above, the reference regions can bederived from the potential reference regions, or vice versa. Forexample, the reference and potential reference regions can correspond tothose described above (e.g., the reference and potential referencepoints illustrated in FIGS. 2A-10).

The algorithm 500 can further involve matching or mapping referenceregions over time in operation 504, for example, between a first dataacquisition and a second or any subsequent data acquisition (i.e.,between any two data acquisitions). In this way, the system 100 cantrack the progression (e.g., improvement, deterioration, or no change)and/or the emergence of dental conditions, diseases, and/or deficienciesover time.

The algorithm 500 can further involve determining a discrepancy (e.g.,numerically and/or graphically) between reference regions over time inoperation 506, for example, between a first data acquisition and asecond or any subsequent data acquisition (i.e., between any two dataacquisitions). In this way, the system 100 can track the progression(e.g., improvement, deterioration, or no change) and/or the emergence ofdental conditions, diseases, and/or deficiencies over time. For example,improvement of an oral feature can correspond to a positive or negativediscrepancy (e.g., an increase or decrease in a value associated withthe reference regions between two data acquisitions). Deterioration ofan oral feature can correspond to a positive or negative discrepancy(e.g., an increase or decrease in a value associated with the referenceregions between two data acquisitions). No change in an oral feature cancorrespond to zero discrepancy, or an approximately zero discrepancy(e.g., no change in a value associated with the reference regionsbetween two data acquisitions).

From operation 506, FIG. 14 illustrates that the algorithm 500 caninvolve diagnosing (or otherwise identifying) the dental conditions,diseases, and/or deficiencies in operation 508, for example, basedpartly or completely on the data determined in operations 502, 504, and506, and can involve determining whether to treat or monitor thediagnosed dental conditions, diseases, and/or deficiencies in operation508.

The algorithm 500 can further involve determining treating the dentalconditions, diseases, and/or deficiencies in operation 510. Treatmentcan involve using sealant, one or patches, crowns, and/or veneers. Thetreatment used can minimize further deterioration, for example, furtherwear, further erosion, further abrasion, further abfraction, or anyother deterioration of the conditions shown and described herein, forexample, those shown and described with reference to FIGS. 2A-10. Thetreatment can recover the original or bring the teeth closer to theiroriginal shape. The treatment can treat the dental conditions, diseases,and/or deficiencies such that the original condition of the teeth is notrepaired, recovered, or otherwise achieved. The treatments applied toone or more teeth can be designed to make the bit more ideal. Forexample, for wear, a temporary cap with a hole can be placed over atooth such that the cap and hole are placed over a reference regionindicating wear. Once placed on a tooth, sealant can be injected throughthe hole such that the cap provides a mold for the sealant when thesealant hardens. The hole can have a one-way valve to prevent sealantfrom discharging from the cap. The temporary cap can be filled withsealant near the hole prior to placement on the tooth adjacent to thewear. The hole can have a one-way valve that allows sealant to exit thespace between the cap and the tooth. During placement, excess sealantcan be forced out of the hole and one way valve such that the sealantthat remains in the cap can harden according to the shape of the cap. Inthis way, wear (e.g., the wear in FIG. 2E) can be treated, for example,by first constructing the cap having the hole, introducing sealant tothe wear location, and hardening the sealant (e.g., with ultrasound).

The algorithm 500 can further involve simulating and/or predicting theprogression of the dental conditions, diseases, and/or deficiencies inoperation 512, with and/or without treatment.

A number of variations have been described. Nevertheless, it will beunderstood by one of ordinary skill in the art that variousmodifications may be made without departing from the spirit and scope ofthe variations. In addition, the flowcharts, logic flows, and algorithmsdepicted in the figures do not require the particular order shown, orsequential order, to achieve desirable results, and are exemplary only.In addition, other steps or operations may be provided, or steps oroperations may be eliminated, from the described flows and algorithms,and other components and/or features may be added to, or removed from,the described and contemplated systems. Accordingly, other variationsare within the scope of the following claims.

It will be understood by one of ordinary skill in the art that thevarious methods and processes disclosed herein may be embodied in anon-transitory readable medium, machine-readable medium, and/or amachine accessible medium comprising instructions compatible, readable,and/or executable by a processor or processing unit of a machine,device, or computing device. The structures and modules in the figuresmay be shown as distinct and communicating with only a few specificstructures and not others. The structures may be merged with each other,may perform overlapping functions, and may communicate with otherstructures not shown to be connected in the figures. Accordingly, thespecification and/or drawings may be regarded in an illustrative ratherthan a restrictive sense.

The claims are not limited to the exemplary variations shown in thefigures, but instead may claim any feature disclosed or contemplated inthe disclosure as a whole. Any elements described herein as singular canbe pluralized (i.e., anything described as “one” can be more than one).Any species element of a genus element can have the characteristics orelements of any other species element of that genus. Some elements maybe absent from individual figures for reasons of illustrative clarity.The above-described configurations, elements or complete assemblies andmethods and their elements for carrying out the disclosure, andvariations of aspects of the disclosure can be combined and modifiedwith each other in any combination. All devices, apparatuses, systems,methods, and algorithms described herein can be used for medical (e.g.,diagnostic, therapeutic or rehabilitative) or non-medical purposes.

1-2. (canceled)
 3. A method of electronically diagnosing and trackingthe progression of one or more dental conditions, the method comprising:determining an oral feature result by processing data of an oralfeature; diagnosing a dental condition of the oral feature based on theoral feature result; and tracking the progression of the dentalcondition over time.
 4. The method of claim 3, wherein processing dataof an oral feature comprises at least one of mapping the oral featureand measuring the oral feature.
 5. The method of claim 3, whereinprocessing data of an oral feature comprises at least one of mapping theoral feature, wherein the mapping is at least one of a current mappingof the oral feature and a predictive mapping of the oral feature.
 6. Themethod of claim 3, wherein processing data of an oral feature comprisesdetecting at least one of a dimension, a contact surface, a shape, acolor, a shade, and a measurement of the oral feature.
 7. The method ofclaim 3, wherein the oral feature result comprises an anatomical markerof the dental condition.
 8. The method of claim 3, further comprisingsimulating at least one of a treatment of the dental condition and theprogression of the dental condition.
 9. The method of claim 3, furthercomprising simulating at least one of the progression of the dentalcondition with treatment of the dental condition and the progression ofthe dental condition without treatment of the dental condition.
 10. Themethod of claim 3, wherein tracking the progression of the dentalcondition over time comprises determining a discrepancy between the oralfeature at a first time and the oral feature at a second time.
 11. Themethod of claim 3, wherein diagnosing a dental condition of the oralfeature comprises at least one of comparing the oral feature result to adatabase of one or more stored oral feature results and comparing theoral feature result to a diagnosis threshold.
 12. A method ofelectronically diagnosing and tracking the progression of one or moredental conditions, the method comprising: diagnosing, via a processor, adental condition based on data of an oral feature; and tracking theprogression of the dental condition by determining a discrepancy betweenthe oral feature at a first time and the oral feature at a second time.13. The method of claim 12, wherein diagnosing, via a processor, adental condition comprises diagnosing the dental condition based on adiagnosis threshold.
 14. The method of claim 12, further comprisingcomparing a diagnosis value associated with the dental condition to atreatment threshold.
 15. The method of claim 14, further comprisingmaking a determination to treat the dental condition if the diagnosisvalue exceeds the treatment threshold.
 16. The method of claim 15,further comprising simulating a treatment of the dental condition. 17.The method of claim 12, further comprising simulating a treatment of thedental condition.
 18. The method of claim 12, further comprisingsimulating at least one of the progression of the dental condition withtreatment of the dental condition and the progression of the dentalcondition without treatment of the dental condition.
 19. The method ofclaim 18, further comprising simulating treatment of the dentalcondition.
 20. A dental condition diagnosis and tracking systemconfigured to: process first and second data sets of an oral feature todetermine a dental condition first feature and a dental condition secondfeature, respectively; diagnose the dental condition upon confirmingthat the dental condition first feature and/or the dental conditionsecond feature is associated with the dental condition; and track theprogression of the dental condition by determining a discrepancy betweenthe dental condition first and second features.
 21. The system of claim20, wherein the system is configured to determine the discrepancybetween the dental condition first and second features by comparingreference regions associated with the dental condition first and secondfeatures.
 22. The system of claim 20, wherein the system is configuredto recommend a modification in treatment of the dental condition basedon the progression of the dental condition.